Learning of fish movement pattern by neural network

Yoshiteru Takezawa; Hidekazu Suzuki; Mamoru Minami; Yasushi Mae

Learning of fish movement pattern by neural network

Yoshiteru Takezawa, Hidekazu Suzuki, Mamoru Minami, Yasushi Mae

Research output: Contribution to conference › Paper › peer-review

Abstract

This paper presents a prediction method of fish movement based on learning its movement by using the Neural Network. The position of a fish is obtained by model-based matching and gazing-GA in real-time. The back-propagation is used for learning and predicting the movement of fish, where fish position is used as the input/teaching signal. The architecture and the internal parameter of the Neural Network are determined by basic experiments which use the simulated movement of fish. Experimental results using a swimming fish show that the proposed method can predict the movement of fish.

Original language	English
Pages	2400-2405
Number of pages	6
Publication status	Published - 2005
Externally published	Yes
Event	SICE Annual Conference 2005 - Okayama, Japan Duration: Aug 8 2005 → Aug 10 2005

Other

Other	SICE Annual Conference 2005
Country	Japan
City	Okayama
Period	8/8/05 → 8/10/05

Keywords

Back-propagation
Gazing-GA
Neural Network
Visual Sarvoing

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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title = "Learning of fish movement pattern by neural network",

abstract = "This paper presents a prediction method of fish movement based on learning its movement by using the Neural Network. The position of a fish is obtained by model-based matching and gazing-GA in real-time. The back-propagation is used for learning and predicting the movement of fish, where fish position is used as the input/teaching signal. The architecture and the internal parameter of the Neural Network are determined by basic experiments which use the simulated movement of fish. Experimental results using a swimming fish show that the proposed method can predict the movement of fish.",

keywords = "Back-propagation, Gazing-GA, Neural Network, Visual Sarvoing",

author = "Yoshiteru Takezawa and Hidekazu Suzuki and Mamoru Minami and Yasushi Mae",

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AU - Suzuki, Hidekazu

AU - Minami, Mamoru

AU - Mae, Yasushi

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N2 - This paper presents a prediction method of fish movement based on learning its movement by using the Neural Network. The position of a fish is obtained by model-based matching and gazing-GA in real-time. The back-propagation is used for learning and predicting the movement of fish, where fish position is used as the input/teaching signal. The architecture and the internal parameter of the Neural Network are determined by basic experiments which use the simulated movement of fish. Experimental results using a swimming fish show that the proposed method can predict the movement of fish.

AB - This paper presents a prediction method of fish movement based on learning its movement by using the Neural Network. The position of a fish is obtained by model-based matching and gazing-GA in real-time. The back-propagation is used for learning and predicting the movement of fish, where fish position is used as the input/teaching signal. The architecture and the internal parameter of the Neural Network are determined by basic experiments which use the simulated movement of fish. Experimental results using a swimming fish show that the proposed method can predict the movement of fish.

KW - Back-propagation

KW - Gazing-GA

KW - Neural Network

KW - Visual Sarvoing

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